Introduction to Computational Complexity
by Martin Tompa
Number of pages: 85
These are the lecture notes from a graduate course on Computational Complexity taught at the University of Washington. This text adopts some approaches that will appear unconventional. For example, alternating Turing machines are introduced very early, and deterministic and nondeterministic Turing machines treated as special cases. This simplifies many proofs, such as that of Savitch's Theorem, the P-completeness of the circuit value problem, the NP-completeness of the satisfiability problem, and the PSPACE-completeness of the quantified Boolean formula problem.
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by Luca Trevisan
Notes from a graduate courses on Computational Complexity. The first 15 lectures cover fundamentals, the remaining is advanced material: Hastad's optimal inapproximability results, lower bounds for parity in bounded depth-circuits, and more.
by Oded Goldreich
Complexity theory is the study of the intrinsic complexity of computational tasks. The book is aimed at exposing the students to the basic results and research directions in the field. The focus was on concepts, complex technical proofs were avoided.
by Allen Downey - Green Tea Press
This book is about data structures and algorithms, intermediate programming in Python, complexity science and the philosophy of science. The book covers Graphs, Analysis of algorithms, Scale-free networks, Cellular Automata, Agent-based models, etc.
by Karl Petersen - University of North Carolina
These notes provide an introduction to the subject of measure-preserving dynamical systems, discussing the dynamical viewpoint; how and from where measure-preserving systems arise; the construction of measures and invariant measures; etc.